A
Alberto Prieto
Researcher at University of Granada
Publications - 248
Citations - 4450
Alberto Prieto is an academic researcher from University of Granada. The author has contributed to research in topics: Artificial neural network & Fuzzy logic. The author has an hindex of 34, co-authored 248 publications receiving 4285 citations. Previous affiliations of Alberto Prieto include Royal Institute of Technology & Cisco Systems, Inc..
Papers
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Journal Article
SSA, SVD, QR-cp, and RBF model reduction
TL;DR: In this paper, the authors proposed an application of SVD model reduction to the class of RBF neural models for improving performance in contexts such as on-line prediction of time series.
Book ChapterDOI
Test Pattern Generation for Analog Circuits Using Neural Networks and Evolutive Algorithms
TL;DR: A comparative analysis of neural networks, simulated annealing, and genetic algorithms in the determination of input patterns for testing analog circuits made possible by using techniques based on neural and evolutive algorithms is presented.
Proceedings Article
What are the main factors involved in the design of a Radial Basis Function Network
Ignacio Rojas Ruiz,Mancia Anguita,Eduardo Ros Vidal,Héctor Pomares,Olga Valenzuela,Alberto Prieto +5 more
Proceedings ArticleDOI
A method for structure identification in complete rule-based fuzzy systems
TL;DR: This paper presents a reliable method to obtain the structure of a complete rule-based fuzzy system that can decide which input variables must be taken into account in the fuzzy system and how many membership functions are needed in every selected input variable in order to reach the approximation target with the minimum number of parameters.
Book ChapterDOI
Monitoring Flow Aggregates with Controllable Accuracy
Alberto Prieto,Rolf Stadler +1 more
TL;DR: The feasibility of real-time flow monitoring with controllable accuracy in today's IP networks is shown, based on Netflow and A-GAP, and the testbed measurements are consistent with simulation studies performed for different topologies and network sizes.